class_docstr: Bounding box type to deal with four co-ordinates for object detection tasks.
  
  Notes
  -----
  *  Although it is explicit and probably familiar to the API consumer systems
     like Javascript to use a dictionary with ``x1, y1, x2 and y2`` as keys, we went
     with DL convention which is to use a list/tuple in which four floats are
     arranged in the same ``order -> x1, y1, x2, y2``
code: def deserialize(self, box: Tuple[float, ...]) -> Tensor:
      tensor = torch.FloatTensor(box)
      self._validate(tensor)
      return tensor
  
file_path: lightning-flash/src/flash/core/serve/types/bbox.py
imports: from dataclasses import dataclass
  from typing import Tuple
  import torch
  from torch import Tensor
  from flash.core.serve.types.base import BaseType
label_desc: Use image node_id 3 for calling the BBox obj's underlying member method code with example usage: obj.deserialize(box) and returns: tensor